There is a desire to provide a way to determine relative skills of players of games such as computer games, chess, tennis, and any other type of game. This needs to be achieved in a manner whereby the indication of relative skill is as accurate as possible and also is understood and accepted by end users (i.e. game players). In addition the relative skills need to be determined quickly even in the case of games involving many players and also in the case of many teams of players, each team having many members. This is particularly problematic because in these situations, computational complexity typically increases significantly. Players can be human players or computer programs.
In our earlier US patent application filed on 24 Jan. 2005 entitled “Bayesian Scoring”, we describe a system for ranking or determining an indication of the skill of a player based on the outcome of a game. The skill levels may be used to track a player's progress and/or standing in the gaming environment, and/or may be used to match players with each other for a future game. We describe a system using Bayesian statistical techniques to determine the indications of player relative skill. The present invention builds on and extends our earlier work and in particular provides a new computational method which enables computation times to be reduced.
A previous ranking system for games has been proposed which uses a statistical approach. The ELO ranking system, devised by Arpad Elo, is suitable for two-player games only. However, it is required to provide a system which works for game modes with more than two players per match.
The present invention seeks to provide an improved method and apparatus for determining an indication of the relative skill of players of a game which overcomes or at least mitigates one or more of the problems noted above.